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Information use and resource
competition: an integrative framework
Alexander E. G. Lee1,2, James P. Ounsley3, Tim Coulson2, J. Marcus Rowcliffe1
and Guy Cowlishaw1
Research
Cite this article: Lee AEG, Ounsley JP,
Coulson T, Rowcliffe JM, Cowlishaw G. 2016
Information use and resource competition: an
integrative framework. Proc. R. Soc. B 283:
20152550.
http://dx.doi.org/10.1098/rspb.2015.2550
Received: 22 October 2015
Accepted: 22 January 2016
Subject Areas:
evolution, ecology, behaviour
Keywords:
information use, social dominance, resource
ecology, decision-making, producer – scrounger
dynamics, individual differences
Author for correspondence:
Alexander E. G. Lee
e-mail: [email protected]
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rspb.2015.2550 or
via http://rspb.royalsocietypublishing.org.
1
The Institute of Zoology, Zoological Society of London, Regent’s Park, London, UK
Department of Zoology, University of Oxford, Oxford, UK
3
School of Biology, University of St Andrews, St Andrews, UK
2
AEGL, 0000-0002-3937-5083; TC, 0000-0001-9371-9003; JMR, 0000-0002-4286-6887;
GC, 0000-0002-7269-4625
Organisms may reduce uncertainty regarding how best to exploit their environment by collecting information about resource distribution. We develop a
model to demonstrate how competition can facilitate or constrain an individual’s
ability to use information when acquiring resources. As resource distribution
underpins both selection on information use and the strength and nature of competition between individuals, we demonstrate interdependencies between the
two that should be common in nature. Individuals in our model can search
for resources either personally or by using social information. We explore selection on social information use across a comprehensive range of ecological
conditions, generalizing the producer–scrounger framework to a wide diversity
of taxa and resources. We show that resource ecology—defined by scarcity,
depletion rate and monopolizability—determines patterns of individual
differences in social information use. These differences suggest coevolutionary
processes linking dominance systems and social information use, with
implications for the evolutionary demography of populations.
1. Introduction
Organisms must secure resources such as food, mates and safety from predation to ensure survival and reproduction. Variability in the spatio-temporal
distribution of these resources means that individuals face uncertainty regarding how best to exploit them. Individuals can thus acquire resources more
efficiently by collecting uncertainty-reducing information [1,2]. However,
resource distribution also underpins the strength and nature of competition
between individuals [3– 5]. Despite this convergence in resource distribution
as a selective force, very little is known about how competition might facilitate
or constrain information use. In this study, we present a general model to predict how resource competition will affect individual information use across a
comprehensive range of ecological conditions, generating novel insights into
the behavioural processes underlying the evolution of social systems.
Information can be gathered either personally, by direct interaction with the
environment, or socially, by observing the behaviours of others [6,7]. The majority
of research into information use has focused on two key ways that the costs and
benefits of ‘personal’ versus ‘social’ information can differ. First, empirical and
theoretical studies have shown that if gathering personal information involves
long search times, trial-and-error sampling or risk-taking, collecting social information can reduce these costs by exploiting the efforts of others [8–10]. Second,
the usefulness of one type of information over the other will depend on how rapidly
each becomes outdated [11–13]. The resultant cost/reliability trade-off between
personal and social information suggests that selection should favour strategies
that balance adaptively an individual’s reliance on each source [7,14].
Individuals may nonetheless be constrained in their ability to use information
due to competition with others over resources, but such limitations have received
& 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.
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2. The model
We model groups of N individuals searching for and consuming
resource patches. Patches contain F resource units. Individuals
can choose to search for patches using one of two mutually exclusive tactics: producing or scrounging. Producers collect and use
personal information, sampling their environment asocially.
The per capita resource discovery rate for producers in a given
‘time step’ is determined by l, which ranges from 0 to 1 and represents ‘scarcity’. The lower the value of l, the more difficult
resources are to find. Scroungers, in contrast, collect and use
social information. They do not contribute to the group’s resource
discovery rate, but exploit patches produced by others. The proportion of the group producing and scrounging is denoted by q
and (1 2 q), respectively.
The total number of patches discovered per time step is given
by lqN—the per capita resource discovery rate for producers
multiplied by the number of producers in the group. Simultaneous resource discoveries occur if lqN . 1, but individual
scroungers can only access a maximum of one discovered
patch per time step. Therefore, when lqN 1, l represents the
ratio of the costs of collecting social versus personal information,
since a scrounger can access a patch each time step, whereas
a producer discovers a patch only every 1/l time steps.
When lqN , 1, however, scroungers only access a patch
every 1/(lqN) time steps. In this case, the ratio of the costs of
collecting social versus personal information will be 1/qN,
since scroungers access each producer’s discovery, while producers only benefit from their own discoveries. Because our
parameters and variables do not change across time steps for
a given group composition, all resource consumption formulae
given below represent rates per time step (i.e. T ¼ 1).
A producer discovering a patch gains a finder’s advantage of
a resource units before any scroungers arrive [24]. The remaining
(F 2 a) resource units, defined as A, are divided between the producer and any scroungers present in proportion to their relative
competitive weights. Patches are fully depleted in the same time
step that they are discovered, meaning that the finder’s share
(a/F) represents the ‘depletion rate’ of a resource patch within
that time step. An individual’s competitive weight is defined as
CWi ¼ ð1 þ N iÞc ,
ð2:1Þ
2
Proc. R. Soc. B 283: 20152550
which quantifies how rapidly social information becomes
outdated following discovery; and (iii) the ‘monopolizability’
of resource patches, which quantifies the degree to which competitors can exclude one another based on differences in
competitive ability [30]. Within this framework, the classic producer–scrounger game is represented by a specific subset of
the environmental conditions considered.
Using this framework, we investigate how individual
decisions to use personal or social information may be affected
or constrained by ecological conditions and individual phenotype. By considering the interactive effects of three dimensions
of resource ecology, we provide general insights into how the
relative costs of not just collecting, but also using, personal
versus social information should influence individual information use. Furthermore, we demonstrate that the individual
benefits of high competitive ability are dependent on more
than just resource monopolizability when individuals face
uncertainty about the spatio-temporal distribution of resources.
As such, patterns of resource ecology may have previously unexpected influences on the character of social systems across taxa.
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little attention. An individual may be free to collect reliable social
information at a relatively low cost, yet its ability to use it may be
mediated by certain phenotypic factors, such as competitive ability. For example, if food patches or breeding territories are both
limited and monopolizable, then the advantages of using social
information may be restricted to socially dominant individuals
(e.g. [15–17]). Since social information has been variously implicated as a regulator of population growth [18], a benefit of group
living [19] and a facilitator of learning and culture [20,21], constraints on its use may have important ecological and
evolutionary consequences.
The producer–scrounger model represents a useful game
theoretical framework for exploring the influence that competition over resources can have on the evolutionary dynamics
of social information use [9,22]. The model considers groups
of individuals searching for and consuming discrete resource
patches by using either personal information (‘producing’) or
social information (‘scrounging’). When playing ‘producer’,
an individual searches for its own resources; when playing
‘scrounger’, it looks for and exploits the discoveries of producers [23]. A well-established insight from producer–scrounger
games, relating to one element of resource distribution, is
that the ‘finder’s share’ should influence optimal levels of
social information use within a group [24]. When producers can
fully deplete a discovery before the arrival of any scroungers—
at which point social information becomes outdated—there
is no benefit to scrounging behaviour. By contrast, when
depletion time is longer, the finder’s share is lower and scrounging becomes more prevalent. Consistent with this, Giraldeau
& Livoreil [25] experimentally demonstrated a positive relationship between the finder’s share and scrounging behaviour in
nutmeg mannikins (Lonchura punctulata).
Two further elements of resource distribution can readily be
incorporated into producer–scrounger games, but have
received limited attention. First, almost all producer–scrounger
models assume that resources are so hard to find that they are
only discovered singly and successively, regardless of the
number of individuals searching for them as producers. However, it is clear that many organisms inhabit environments in
which simultaneous resource discoveries are likely. Those few
studies that have varied the difficulty of resource discovery
such that simultaneous resource discoveries can occur [26–28]
propose that social information use should decrease as finding
resources using personal information becomes easier. Second,
only one model [29] has explored the effects of resource
monopolizability on scrounging behaviour, while others have
assumed scramble-like competition between a producer and
any scroungers at its discovery. Barta & Giraldeau [29] demonstrated a positive link between dominance and scrounging
behaviour when resources were monopolizable.
No study to date has attempted to combine the three
elements of resource distribution outlined above to better
understand how their influences on the strength and nature
of competition might interact to impact individual information
use. Such an approach should be of general interest given the
range of ecological conditions that different taxa experience
when exploiting resources in nature. Here, we expand the producer–scrounger game to develop a general model for how
resource ecology should affect individual information use in
a social context. We define resource ecology along three axes
of variation: (i) the ‘scarcity’ of resource patches, which quantifies how difficult they are to discover using personal
information; (ii) the ‘depletion rate’ of resource patches,
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where P is the set of social ranks for all qN individuals playing producer, making CWk the competitive weight of the kth
producer in the set. The summation operator describes a
scrounger accessing the discoveries of all qN producers in
the group.
When lqN . 1, scroungers cannot access all discoveries,
since some discoveries are occurring simultaneously. As
such, we assume that the probability of a scrounger exploiting a given producer’s discovery in each time step is
determined by the total number of discoveries in the group,
which we take to be the expected value of lqN. While lqN
will in reality also be probabilistic, modelling its expected
(i.e. mean) value will not have affected the model’s overall
predictions, but allowed us to focus on how scroungers
may be distributed probabilistically across different producers. A given producer is at risk of being exploited by a
total of n ¼ (1 2 q)N mutually independent scroungers,
where the likelihood of each of these scroungers being present is thus 1/lqN. The probability of a given producer
being scrounged by a certain number, l, of the n scroungers
is drawn from a binomial distribution. However, the identities of the l scroungers exploiting a producer will influence
the cumulative competitive weight of the individuals within
a patch. We thus calculate the probability of occurrence and
cumulative competitive weight for all 2n possible combinations of scroungers that can occur at a given producer’s
discovery. We define a 2n n matrix, SP, which defines the
absence (0) or the presence (1) of each scrounger for each
combination. The probability of occurrence for each of these
3
1 l
1 nl
1
,
lqN
lqN
ð2:4Þ
where the value of l for each row is the sum of the elements in
the corresponding row in SP. To calculate the cumulative
competitive weight of scroungers for each combination, we
multiplied SP by a n 1 column vector, CP, of competitive
weights for each individual scrounger, to produce a 2n 1
column vector, WP, of competitive weights summed across
scroungers for each possible combination of individual
scroungers present.
As such, when lqN . 1, the rate of resource consumption
for the ith-ranking producer is given by
!
2n
X
CWi
IP,i ¼ lT a þ
b p,m A
,
ð2:5Þ
CWi þ w p,m
m¼1
where bp,m and wp,m represent the mth elements (i.e. rows)
of the BP and WP, vectors, respectively, and m ranges from
1 to 2n.
To calculate the rate of resource consumption for a given
scrounger, we must define all of the possible contexts in
which it can be when exploiting producers. For each context,
we calculate its probability of occurrence and the cumulative
competitive weight of individuals present. A scrounger will
always exploit one producer when lqN . 1. This may occur
alone or in conjunction with a certain number, (l 2 1), of the
remaining (n 2 1) scroungers. The total number of possible
combinations of other scroungers occurring alongside a given
focal scrounger is 2(n21). We define a 2(n21) (n 2 1) matrix,
SS, which records the absence (0) or the presence (1) of the
remaining scroungers for each combination. The likelihood of
any individual scrounger exploiting a given producer is
1/lqN, making the probability of a given scrounger sharing a
resource with a given combination of the remaining scroungers
1 ðl1Þ
1 ðn1Þðl1Þ
1
:
lqN
lqN
ð2:6Þ
Since the focal scrounger will itself only have a 1/lqN
chance of being present at a given producer’s discovery, the
probability of each of these combinations occurring at a
given discovery will be
1 ðl1Þ
1 ðn1Þðl1Þ 1
1
,
lqN
lqN
lqN
ð2:7Þ
simplified as
1 ðlÞ
1 ðnlÞ
1
:
lqN
lqN
ð2:8Þ
We calculate this probability for each of the 2(n21) possible
combinations to produce a 2(n21) 1 column vector, BS.
The identity of a given focal scrounger will influence the
cumulative competitive weight of the (n 2 1) remaining
scroungers. As such, we define, for each focal scrounger, a separate (n 2 1) 1 column vector, CSi, of competitive weights for
the remaining scroungers, where i is the rank of the focal
scrounger. The cumulative competitive weight of remaining
scroungers for each of the 2(n21) combinations is calculated
for the ith-ranking scrounger by multiplying the matrix SS
Proc. R. Soc. B 283: 20152550
where S is the set of social ranks for all (1 2 q)N individuals
playing scrounger, and CWj is the competitive weight of
P
the jth scrounger in the set, making
j[S CWj the summed
competitive weight of all scroungers in the group. The rate
of resource consumption for the ith-ranking scrounger, in
contrast, is
!
X
CWi
P
IS,i ¼ lTA
,
ð2:3Þ
CWk þ j[S CWj
k[P
combinations is given in a 2n 1 column vector, BP, the
elements of which are calculated as
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where i denotes an individual’s ranked competitive ability relative to others in the group (expressed as an integer, ascending
from 1 to N; hereafter ‘social rank’), and c defines the degree to
which patches can be monopolized [29].
The exponent c represents resource ‘monopolizability’, and
may be best considered as patch area. When c ¼ 0, an individual cannot monopolize a patch regardless of social rank; CWi is
the same for all individuals, and competition at patches is
scramble-like. However, as c increases, resources become
more defensible and the degree to which social rank influences
competitive asymmetry between individuals increases following a power law. When c ¼ 100, the highest-ranking individual
in a patch essentially monopolizes A.
If lqN 1, scroungers are able to access each patch discovery. In this case, the rate of resource consumption for
producers and scroungers is equivalent to that given by
Barta & Giraldeau [29]. When, in addition to this, c ¼ 0,
the model becomes equivalent to the classical producer –
scrounger game [23,24]. The rate of resource consumption
for the ith-ranking producer with competitive weight CWi
when lqN 1 is given by
!
CWi
P
IP,i ¼ lT a þ A
,
ð2:2Þ
CWi þ j[S CWj
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Pi ¼
Ii
ðSN
r¼1 Ir =NÞ
,
ð2:10Þ
its fitness relative to the group’s average. In this way, we
searched for Nash equilibria: stable group compositions
where no individual could increase its payoff by switching
tactic. We generated results numerically across a range of
group sizes (4, 8, 16), but our equations relate to groups of
any size. Here, we present only those findings where N ¼ 16,
since the other group sizes modelled always showed qualitatively similar patterns. The robustness of our findings to
increasing group size is corroborated by our analysis of a
larger range of group sizes (ranging from 4 to 28) across a pertinent range of the parameter space, the results of which are
presented in the electronic supplementary material.
We began each model run by defining a group as a vector
of zeros and ones of length N, where the value at position i
represents the tactic (0 ¼ producer; 1 ¼ scrounger) of the
ith-ranking individual [29]. Initial group composition was
generated such that each individual had a 50% chance of
starting as a producer or scrounger. The group was then perturbed by randomly selecting one individual to switch tactics.
If this individual’s payoff increased, the new tactic would be
maintained; otherwise, it would revert to its previous tactic.
This perturbation was repeated until a Nash equilibrium
was reached. Model runs for a given parameter set were
replicated up to 10 000 times in order to account for multiple
Nash equilibria. We thus calculated—for each group and
each individual in each parameter set—the probability of
scrounging based on average tactics in the stable group compositions of model replicates. All model analysis was
conducted in R v. 3.0.2 [31].
3. Results
Increasing the producer’s resource discovery rate (l ) reduced
the relative cost of collecting personal information. However,
the impact of this relationship on the decision to produce or
scrounge was dependent upon resource monopolizability.
When individuals were unable to monopolize resources (i.e.
c ¼ 0), scrounging became less common if patches were easier
to find (higher l ) (figure 1). Under these conditions, there
was no between-individual variation in scrounging behaviour
(figure 2a). Scrounging ultimately disappeared from the population (i.e. producing became fixed) when resources were
4
proportion scrounging
0.8
0.6
0.4
0.2
0
0
0.2
0.4
0.6
0.8
1.0
per capita resource discovery rate (l)
Figure 1. The combined influence of resource scarcity and monopolizability on
levels of scrounging in a group. Simultaneous resource discoveries occurred only
within the shaded region (i.e. where lqN . 1). Values of c as follows: 0 (black
circles), 1 (orange triangles), 10 (blue crosses), 100 (green diamonds). N ¼ 16;
a/F ¼ 0.05.
sufficiently easy to find using personal information that the
associated costs of resource sharing were no longer economical.
As resources became monopolizable (increasing c), the
relationship between the discovery rate and the proportion
of scrounging in a population changed dramatically. First,
when the discovery rate was low, such that no more than
one patch was being discovered per time step (lqN 1),
scrounging became less common at higher values of c
(figure 1). This occurred because the more effectively every
discovery could be monopolized by a single, top-ranked
individual playing scrounger, the less profitable this tactic
became for others (figure 2a–d, far left columns). Rather,
other individuals would benefit more from playing producer:
even though patch discoveries would be rare, and would be
largely appropriated by the dominant scrounger, producers
would at least secure a finder’s advantage.
Second, under conditions of strong monopolizability (c 10),
intermediate discovery rates promoted higher levels of
scrounging despite the lower relative cost of collecting personal information (figure 1). This was because simultaneous
resource discoveries (i.e. lqN . 1) could occur more easily
as l increased. Simultaneous resource discoveries precluded
complete monopolization by single individuals, freeing
up resources for other individuals to scrounge. Owing to the
higher competitive weights of higher-ranking individuals,
however, scrounging remained tightly linked to social rank
despite more individuals being able to use the tactic
(figure 2c,d). Finally, scrounging began to decline once
resources became so easy to find that even the highest-ranked
individuals would benefit more from producing—thus gaining
a finder’s advantage—than from monopolizing the discoveries
of others (figure 1). The overall result when c 10 was thus a
‘peaked’ relationship between resource discovery rate and
population levels of scrounging.
Scrounging was less common when the finder’s share was
high (figure 3). Individuals were less likely to scrounge as those
producing benefited from consuming greater portions of their
discoveries, leaving less for scroungers to exploit. The strength
of this effect, however, was influenced by both resource discovery rate and monopolizability. While at very small finder’s
Proc. R. Soc. B 283: 20152550
where bs,m and wsi,m represent the mth elements (i.e. rows) of the
BS and WSi vectors, respectively, and m ranges from 1 to 2(n21).
The competitive weight of a given producer, CWk, is defined
as above.
We analysed the model—for fixed values of N, a/F, l and
c—by allowing individuals to switch between the producer
and scrounger tactic in an attempt to improve their relative
rate of resource consumption, or relative fitness. This was
calculated for the ith-ranking individual as
1.0
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with the column vector CSi, to generate a 2(n21) 1 column
vector, WSi.
When lqN . 1, therefore, the rate of resource consumption
for the ith-ranking scrounger is given by
!
ðn1Þ
X 2X
CWi
IS,i ¼ lT
bs,m A
,
ð2:9Þ
CWk þ CWi þ wsi,m
k[P m¼1
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(b)
p(scrounge)
1.00
0.75
0.50
0.25
0
social rank
(c)
5
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
p(scrounge)
1.00
0.75
0.50
0.25
0
(d)
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
p(scrounge)
1.00
0.75
0.50
0.25
0
0.01 0.1 0.3 0.5 0.7 0.9 1.0
per capita resource discovery rate (l)
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
p(scrounge)
1.00
0.75
0.50
0.25
0
0.01 0.1 0.3 0.5 0.7 0.9 1.0
per capita resource discovery rate (l)
Figure 2. The combined effect of resource scarcity and monopolizability on the probability of scrounging for individuals of different social rank. Resource monopolizability for each panel as follows: (a) c ¼ 0 (black), (b) c ¼ 1 (orange), (c) c ¼ 10 (blue) and (d ) c ¼ 100 (green). Colour coding corresponds to that given in
figure 1. Note that social rank ranges highest to lowest from 1 to N. N ¼ 16; a/F ¼ 0.05.
shares the levels of scrounging were usually lower when monopolizability was high, the rate of decline of scrounging with
increasing finder’s share was actually slower at higher levels
of monopolizability (figure 3a–d). This reflects the fact that
scroungers able to monopolize patches were more robust to
the losses associated with a higher finder’s share, because
they still secured large proportions of the remaining A resource
units. By contrast, the general effect of a higher resource discovery rate was to accelerate the decline in scrounging associated
with the finder’s share (figure 3a–d). When resources could
be discovered more easily, individuals benefited from producing when the finder’s share was high.
Finally, high resource monopolizability allowed scrounging
to persist at intermediate values of the finder’s share when it
would otherwise disappear from the population (figure 3b),
although this effect persisted only at progressively smaller
values of the finder’s share as discovery rates increased
(figure 3c,d). This was caused by a combination of simultaneous
resource discoveries and the robustness of scrounging for
individuals of high social rank described above.
The interactive effects of resource discovery rate and monopolizability on scrounging behaviour had important fitness
consequences (figure 4). The exclusivity of scrounging to individuals of high rank when resources were monopolizable but
extremely rare resulted in a strong skew in fitness favouring
dominant individuals. This increased in proportion with c,
and tended towards a single, top-ranked scrounger with a
very high relative fitness (figure 4d, far-left column). As
resources became easier to find, however, this fitness skew
became less dramatic (figure 4d). This was primarily due to
the occurrence of simultaneous resource discoveries, which
made scrounging behaviour and its benefits more evenly
shared across more individuals of relatively high social rank,
and lower-ranked producers less prone to being in direct competition with the highest ranked individuals. Low-ranked
producers also benefited from more frequent discoveries, and
the resulting finder’s share benefits, when the discovery rate
was high. These findings were in stark contrast to the outcome
when resources could not be monopolized (c ¼ 0). In these
cases, there was no variation in scrounging propensity between
individuals, leading the population to a stable mix of producers and scroungers where all individuals had equal fitness
irrespective of social rank or resource scarcity (figure 4a).
Since scroungers do not contribute to resource discovery,
they can reduce a population’s average individual resource
consumption rate, potentially impacting on various demographic processes. When resources were rare (i.e. low l ),
higher values of c resulted in fewer scroungers and therefore
greater average intake rates (figure 5). However, as resources
became more common this pattern reversed: high values of c
led to more scroungers and thus lower average intake rates
relative to when c was low.
4. Discussion
Our aim was to explore the interdependencies between
information use and competition over resources, driven by
Proc. R. Soc. B 283: 20152550
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7
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social rank
(a)
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(b)
1.0
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
1.0
(d)
1.0
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0
0
proportion scrounging
(c)
0
0.2
0.4
0.6
finder’s share (a/F)
0.8
1.0
6
Proc. R. Soc. B 283: 20152550
1.0
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proportion scrounging
(a)
0
0.2
0.4
0.6
finder’s share (a/F)
0.8
1.0
Figure 3. The effect of the finder’s share on levels of scrounging in a group depends on interactions between resource scarcity and monopolizability. Panels
show data for different values of per capita resource discovery rate (l ) as follows: (a) 0.01, (b) 0.3, (c) 0.5 and (d ) 0.9. Values of c as follows: 0 (black circles),
1 (orange triangles), 10 (blue crosses), 100 (green diamonds). Simultaneous resource discoveries occurred only within the shaded regions (i.e. where lqN . 1).
N ¼ 16; a/F ¼ 0.05.
resource distribution as a shared selective force. To do this,
we investigated how three key aspects of resource ecology—
scarcity, depletion rate and monopolizability—interact to
promote or constrain the use of social information when
acquiring resources in an uncertain environment. Further, we
asked how such influences might lead to variation in fitness
between individuals through differential access to resources.
Our findings generated two key predictions. First, the effects
of resource scarcity on social information use should depend
strongly on resource monopolizability. Second, the potential
benefits of social dominance should be closely linked to
social information use in uncertain environments, determined
not just by monopolizability, but all three aspects of resource
ecology. Below, we discuss these predictions in the context
of previous work and propose avenues for future research.
We then raise an important theoretical consideration for
the study of social information use, and conclude by outlining the potential evolutionary demographic implications of
our research.
Previous producer–scrounger models have proposed that
individuals should rely more on social information when the
costs of collecting personal information are high (i.e. scrounging increases as valuable resources become harder to find)
[26–28,32]. Although this relationship seems intuitive, direct
experimental support is surprisingly lacking [14], possibly
because the true relationship is dependent on the degree of
resource monopolizability. Thus, our results confirmed this
pattern when resources were not monopolizable, but predicted
a ‘peaked’ relationship when resources were monopolizable,
where social information use (scrounging) only increases
initially but then declines again as resources become progressively scarcer. Data from Koops & Giraldeau [33] provides
circumstantial evidence supporting this explanation. These
authors found that scrounging declined in European starlings
(Sturnus vulgaris) when novel food patches were more scarce,
contrary to conventional wisdom but consistent with the
downturn our model predicts at higher levels of resource scarcity and monopolizability. Crucially, starling social groups
exhibit a dominance structure [34], and Koops & Giraldeau
[33] reported that scroungers in their study were primarily
socially dominant starlings with a competitive advantage at
resource patches. Our findings thus suggest that resource scarcity, depletion rate and monopolizability should be considered
in unison when making predictions about how selection
should act on social information use in a given species.
Most research into information use has focused on how
individuals optimize their reliance on social versus personal
information based on trade-offs between their collection costs
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log(fitness)
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Figure 4. Resource scarcity and monopolizability interact to determine both the skew and strength of the fitness benefits of social rank. Resource monopolizability
for each panel as follows: (a) c ¼ 0 (black), (b) c ¼ 1 (orange), (c) c ¼ 10 (blue) and (d ) c ¼ 100 (green). Colour coding corresponds to that given in figure 1.
Note that social rank ranges highest to lowest from 1 to N. N ¼ 16; a/F ¼ 0.05.
and reliabilities [14,20], and their negatively frequencydependent payoffs [23]. Very little attention has been given
to the constraints that competition imposes on an individual’s
liberty to use social information to access resources. Our findings are consistent with the only previous study to consider
systematically how variation in competitive ability might constrain individual social information use due to competition
over limited resources [29]: when resources are monopolizable,
social information use may become exclusive to dominant individuals, leading to a positive relationship between social rank
and resource acquisition rate. However, our model further
demonstrates that resource scarcity is critical in determining
the degree of this exclusivity. Specifically, it is only under conditions of sequential resource discovery that a single individual
can make exclusive use of social information; when resources
are discovered simultaneously social information may be
exploited by successively lower ranked individuals.
Despite the clear influence that social dominance may
play in constraining information use, we know of no studies
exploring how social information use varies in response to
systematic manipulation of resource monopolizability in
taxa exhibiting dominance hierarchies. Liker & Barta [35]
showed that dominant house sparrows (Passer domesticus)
scrounged more than subordinates when searching for
spatially clumped seeds, but did not investigate conditions
where resources could not be monopolized. A number of
other experimental producer –scrounger studies in birds
and primates have reported either a positive relationship
or no relationship between social rank and scrounging
[17,36,37]. Consistent with our findings, observational studies
in chacma baboons have shown that dominance-linked
scrounging increases when food patches are monopolizable
[16,38]. Our model suggests that predictions (and associated
experimental designs) regarding the relationship between
social dominance and information use for a given taxon
should be guided by an appreciation of resource scarcity,
depletion rate and monopolizability. Further empirical
work is needed to experimentally test the predictions that
resource monopolizability constrains an individual’s use of
social information according to dominance, leading to differential access to resources, and that the patterns of these
constraints is dependent on resource scarcity.
The fact that resource monopolizability influences the
benefits of dominance is well established [30,39,40]. However,
since there is expected to be uncertainty associated with the
spatio-temporal distribution of most resources, our model highlights a crucial role for social information use in capturing the
benefits of dominance. As such, selection pressures on dominance will depend on multidimensional aspects of resource
ecology (e.g. scarcity, depletion rate and monopolizability)
that influence both the benefits of social information use and
competition between individuals. This does not mean that we
predict the ecology of any single resource to lead to any particular information use phenotype or social system, since organisms
must exploit many different resources to survive and reproduce.
Overall selection on these phenotypes and systems will be
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mean intake rate
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0.4
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1.0
Figure 5. Resource scarcity and monopolizability affects a group’s average
resource consumption rate through their influence on scrounging behaviour.
Values of c as follows: 0 (black circles), 1 (orange triangles), 10 (blue crosses),
100 (green diamonds). N ¼ 16; a/F ¼ 0.05.
driven by the combined pressures of multiple resources
ecologies through space and time [41].
Our findings also highlight an important theoretical issue
that requires development if we are to fully understand the
evolutionary ecology of social information use. We only consider the acquisition of ephemeral resources that are fully
depleted upon discovery. Like most previous theory, we
thus assume that any information generated by the discovery
of a resource becomes useless upon its depletion. Yet, it is
clear that many organisms exploit resources that exhibit at
least some spatio-temporal predictability, such that previous
experience, or prior information, can be used to inform
future decisions [10,42 –44]. When information is reusable
or generalizable in this way, the relationship between social
information use and competition over resources may
change dramatically. Specifically, social information use
may be decoupled from the context in which it was collected
in a way that would not be possible with unpredictable,
ephemeral resources (where information must be used as
soon as it is collected). For example, an individual may
be able to collect social information in a highly competitive
situation and then use it in a less competitive one. In this
way, competitive constraints on social information use
may be relaxed or altered. Since the fitness benefits of information use are generally expected to be associated with
Data accessibility. Data are available to download from Dryad: http://
dx.doi.org/10.5061/dryad.mn36c.
Authors’ contributions. A.E.G.L. conceived the study, designed and
analysed the model, and drafted the manuscript. J.P.O., T.C.
and J.M.R. provided conceptual input, assisted mathematically and
helped draft the manuscript. G.C. conceived and coordinated the
study, and helped draft the manuscript.
Competing interests. We have no competing interests.
Funding. This study was supported by an NERC Quota Studentship
(NE/J500409/1) awarded to A.E.G.L.
Acknowledgements. Thanks to Alecia Carter, Harry Marshall, Elise
Huchard, Alice Baniel, Jon Bielby and three anonymous reviewers
for their helpful comments on previous versions of this manuscript.
We would like to acknowledge the use of the University of Oxford
Advanced Research Computing (ARC) facility in carrying out this
work. We also thank Daniel van der Post for useful discussions,
and Hannah Wilmot for her assistance with figure formatting.
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